Investigation of Multiple-Dynein Transport of Melanosomes by Non- Invasive Force Measurement Using Fluctuation Unit 

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Investigation of Multiple-Dynein Transport of Melanosomes by Non- Invasive Force Measurement Using Fluctuation Unit  Title: Investigation of multiple-dynein transport of melanosomes by non- invasive force measurement using fluctuation unit Shin Hasegawa1, Takashi Sagawa2, Kazuho Ikeda3, Yasushi Okada3,4,5, and Kumiko Hayashi1,* 1Department of Applied Physics, Graduate School of Engineering, Tohoku University, Sendai, Japan 2Advanced ICT Research Institute, National Institute of Information and Communications Technology, Kobe, Japan 3Laboratory for Cell Dynamics Observation, Center for Biosystems Dynamics Research, RIKEN, Osaka, Japan 4Department of Physics and Universal Biology Institute, Graduate School of Science, The University of Tokyo, Tokyo, Japan 5Department of Physics, Universal Biology Institute, and the International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Tokyo, Japan *Correspondence: [email protected] (K.H.) 1 Pigment organelles known as melanosomes disperse or aggregate in a melanophore in response to hormones. These movements are mediated by the microtubule motors kinesin-2 and cytoplasmic dynein. However, the force generation mechanism of dynein, unlike that of kinesin, is not well understood. In this study, to address this issue, we investigated the dynein-mediated aggregation of melanosomes in zebrafish melanophores. We applied the fluctuation theorem of non-equilibrium statistical mechanics to estimate forces acting on melanosomes during transport by dynein, given that the energy of a system is related to its fluctuation. Our results demonstrate that multiple force-producing units cooperatively transport a single melanosome. Since the force is generated by dynein, this suggests that multiple dyneins carry a single melanosome. Cooperative transport has been reported for other organelles; thus, multiple- motor transport may be a universal mechanism for moving organelles within the cell. 2 Introduction Cellular cargo is transported through the microtubule network of eukaryotic cells by motor proteins1,2. This active transport system delivers materials more rapidly than the passive transport by diffusion occurring in prokaryotic cells. The importance of cargo transport is underscored by the fact that defects in this process in neurons are associated with neuronal diseases such as Alzheimer’s, Parkinson’s, and Huntington’s disease3,4. Multiple-carrier (motor) transport of cargo has recently been proposed5-13 as a mechanism for maintaining the stability of the intracellular transport system by increasing physical quantities such as force and run length. Since the cytosol has a higher viscosity than water14-16, a significant amount of force must be generated through cooperation of multiple motors to overcome friction and haul cargo in cells. In order to investigate force generated by motors acting on a single cargo, a non- invasive force measurement11-13 was recently developed based on the fluctuation theorem of non-equilibrium statistical mechanics17-22. Fluctuation in small systems is not merely due to random motion, but is related to system energetics through physical theorems. The position of a moving cargo can be obtained non-invasively by fluorescence microscopic observation of cells, and the fluctuation of its position is easily observed with high time resolution. Using this fluctuating motion, a fluctuation unit (χ) constructed based on the fluctuation theorem is calculated as a force indicator11-13. The physical background of χ was explained and discussed in the reference13. The parameter χ was previously measured for the transport of synaptic vesicle precursors (SVPs) by the kinesin superfamily protein UNC-104 in the DA9 neuron of Caenorhabditis elegans12. In wild-type worms, the distribution of χ was spread over several clusters, implying the existence of several force-producing units (FPUs); this in turn indicates that a single SVP was carried by multiple UNC-104 motors, which are the generators of force. Measurements of χ revealed that mutant worms lacking ARL-8—an SVP-bound Arf-like small guanosine triphosphatase that relieves the autoinhibition of the motor, which is critical for avoiding unnecessary consumption of ATP when the motor is not bound to an SVP23—had fewer FPUs than their wild-type counterparts12. In this study, we investigated χ for the transport of melanosomes, organelles filled with the melanin pigment, in zebrafish melanophores. Melanosomes are transported by microtubule motors, kinesin-2 and cytoplasmic dynein, and the actin motor myosin-V24. They disperse or aggregate in response to hormones in melanophores. The primary physiological purpose for movement of melanosomes in animals is colour change. Particularly, we focused 3 on the aggregation process of melanosomes transported by dynein. There are several advantages of measurement of χ in this transport system. Firstly, because melanin pigment is black and easily observed by bright-field microscopy, the recording rate can be increased up to 800 frames per second (fps). Such a high-speed recording enables accurate measurement of fluctuation in the position of melanosomes. Secondly, we can decrease the number of dynein motors using the inhibitor ciliobrevin, which was recently identified25 and investigated for many biological phenomena related to dynein25-29, thereby allowing observation of the behaviour of fluctuation unit χ in response to the decrease in motors. Thirdly, the force generation mechanism of dynein is still controversial and therefore worth studying. The stall force value for a single dynein molecule was reported to be 1 pN9,10,30, though a few studies have reported values of 5–10 pN31-33. Fourthly, the behaviour of χ remains to be evaluated in non-neuronal cells. When considered together, melanosome transport is a suitable system to explore χ. In our experiments, the quantal behaviour of χ was observed in melanosome transport by dynein. We concluded that several FPUs carry a single melanosome similarly to cargo transport in neurons11-13. Further, we found that the number of FPUs measured by χ was dramatically decreased by the addition of ciliobrevin, as expected. We anticipate that the non- invasive force measurement using the fluctuation unit (χ) will be applied to a wide range of cargo transport in eukaryotic cells to elucidate the physical mechanisms in which some human diseases are deeply rooted. 4 Results Observation of melanosome transport Melanophores removed from zebrafish scales by enzymatic treatment were cultured in a glass- bottom dish. After 1 day of culture, the motion of melanosomes was observed by bright-field microscopy. Following addition of hormone (epinephrine) to the dish, melanosomes aggregated to the centre of a melanophore. Because the minus ends of microtubules are attached to the centrosome, the motion towards the nucleus is caused by the action of dynein. A schematic of this transport is represented in Fig. 1. Although they were crowded at the start of migration, individual melanosomes could be tracked after several tens of seconds, when nearly all melanosomes were aggregated. The direction of movement was set as the plus X direction (e.g. red line in Fig. 2a). Except for melanosomes close to the nucleus where cells had greater thickness, we considered that the motion in the Z direction was less than that in the X-Y plane since the images of melanosomes were focused during the runs. The centre position (X) of the melanosome was calculated from the recorded images, and the time course of X was obtained (Fig. 2b). Directional movement was defined as movement at a velocity greater than 100 nm/s, as in a previous study on pigment granule transport5. The fluctuation in melanosome position during directional transport, which was observed at a high recording rate of 800 fps (inset in Fig. 2b), was mainly due to thermal noise, stochastic stepping of motors accompanied by ATP hydrolysis, and collision of melanosomes with other organelles and cytoskeletons. Calculation of for melanin pigment transport The constant velocity segment (red area in Fig. 2b) of the position (X) of a melanosome lasting 0.5–1 s was identified by visual inspection for calculation of the fluctuation unit χ (equation (4)). The effect of this selection on the calculation of χ was later evaluated by the bootstrapping method. Based on this segment, we calculated X = X(t + t) − X(t) (e.g. inset in Fig. 2b) and its probability distribution (P(X)) (Fig. 2c for the case t = 37.5 ms), where the value of t ranged from 1.25 to 37.5 ms. P(X) was well fitted by a Gaussian function (solid black curve in Fig. 2c). Because X < 0 could not be observed for a large t because of the limitations of our experiment, P(X) for X > 0 was fitted with a Gaussian function to calculate the ratio P(X)/P(–X) in equation (4). The Gaussian function (equation (5)) was used to fit P(X) after evaluating the Brownian noise power spectrum density S(f) (equation (11)) of X for small f (Supplementary Fig. S1). defined in equation (4) was calculated using equation (6) for each t (Fig. 2d); as a 5 function of t converged to a constant value (*) after relaxation ( 20 ms), which is attributable to the microscopic environment around the melanosome as well as the enzymatic cycle time13. Note that from a physical point of view, the convergence implied that the macroscopic motion of X whose time scale is about 20 ms obeys the simple equation (3). Then, equation (7) was considered for the constant value *. The error of * according to range selection of the constant velocity segment was estimated to be 15% based on the principle of bootstrapping. We first selected 10 different partial segments from the original constant velocity segments; was then calculated for each partial segment (thin curves in Fig. 2d). It should be noted that the length of partial segments was half that of the original segment. Melanosome transport by multiple dynein motors The procedures carried out in Fig. 2b–d for a single melanosome were repeated for 62 different melanosomes from two different melanophore preparations. The calculated values of for the 62 melanosomes are shown in Fig. 3a.
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